Regional Versus Individual Aspects of the Digital Divide in Germany

Abstract

This paper analyzes the regional dimension of the German digital divide. It considers the impact of regional characteristics on differences in the share of Internet use between German counties. In addition, it studies the influence of regional factors as well as individual characteristics on the individual probability of becoming a new Internet user. Based on two large data sets, SOEP and INKAR, the analyses show that it is not the rusticity of a region itself that explains regional differences in Internet use. The results rather indicate that it is the different composition of the population between rural and urban areas that accounts for the regional digital divide.

Determinants of Internet use in Spain

“…The inclusion of these types of variables usually seeks to explain geographical disparities in Internet adoption. Some studies, such as those by Vicente and López (2006) and Demoussis and Giannakopoulos (2006) for the European countries and by Schleife (2006) for German regions, aim to explain differences in Internet use by highlighting the role of different aggregate variables. These studies consider variables related to the level of economic development, such as GDP per capita, the rate of unemployment, trade openness, R&D intensity (R&D expenditure, patents and employment in high-technology sectors) as well as variables related to sectoral composition (percentage of employment in the services sector, agriculture and industry).…”

“…For the German regions, Schleife (2006) finds that individual characteristics are more important than regional factors in explaining individual decisions to use the Internet. In fact, only the percentage of monoparental families, as well as the rate of unemployment, influences the probability of becoming a user.…”

Eficiencia energética en escuelas españolas como indicador de competencia de gestión económica: Diferencias entre centros públicos y privados

“…Hemos procedido a una estimación de un modelo que considera los determinantes de la probabilidad de que una escuela tenga la tecnología en cuestión o no. Con esta técnica, los individuos (escuelas en nuestro caso) eligen entre adoptar esta tecnología (Yi = 1) o no (Yi = 0), habiéndose utilizado esta técnica en varias investigaciones en el campo de la adopción de innovaciones (Vicente y López, 2006;Schleife, 2006;Grazzi y Vergara, 2008).…”

A knowledge-driven shift in perception of ICT implementation barriers: Comparative study of US and European SMEs

“…Available data are usually examined against socio-economic variables such as: gender, age, income, education and ethnicity [4][5]. There is also emphasis on spatial [6][7][8][9] or regional [10][11][12] differentiation of the divide, which led to the introduction of new terms like dual/double digital divide or urban digital divide.…”